Design and simulation of a fuzzy-PID composite parameters' controller with MATLAB
Changhua Lu, Jing Zhang
Abstract
Changhua Lu, Jing Zhang
Abstract
In this paper, we propose a Fuzzy-PID composite parameters' controller. Fuzzy control based on human language and habits of mind belongs to Intelligent Control, is applicable in automatic control field in complex system without accurate mathematic model. However, general fuzzy controller has steady-state static error. While PID can eliminate static error and principle is simple, easy to use and good robustness, PID is introduced into fuzzy control to form a new controller. In this paper we introduce how to design fuzzy controller and PID controller in detail and how to model in MATLAB and use Fuzzy Toolbox and SIMULINK in MATLAB to realize the computer simulation of parameters control system. The computer simulation result shows that Fuzzy-PID composite parameters' controller improves the dynamic and static quality of control system and has more precise control. Fuzzy Toolbox and SIMULINK in MATLAB are effective tools on computer simulation.
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In this paper, we propose a Fuzzy-PID composite parameters' controller. Fuzzy control based on human language and habits of mind belongs to Intelligent Control, is applicable in automatic control field in complex system without accurate mathematic model. However, general fuzzy controller has steady-state static error. While PID can eliminate static error and principle is simple, easy to use and good robustness, PID is introduced into fuzzy control to form a new controller. In this paper we introduce how to design fuzzy controller and PID controller in detail and how to model in MATLAB and use Fuzzy Toolbox and SIMULINK in MATLAB to realize the computer simulation of parameters control system. The computer simulation result shows that Fuzzy-PID composite parameters' controller improves the dynamic and static quality of control system and has more precise control. Fuzzy Toolbox and SIMULINK in MATLAB are effective tools on computer simulation.
Key concepts: PID controller, MATLAB, Control theory (sociology), Robustness (evolution), Fuzzy logic, Computer science, Control engineering, Fuzzy control system